Kai - I think that it depends on the AI company in question. I think there are different moats each could attempt to build instead of all AI companies falling under a single moat. Some examples:
-Marketplaces often leverage AI (e.g. Amazon's recommendation engine).
-Many companies with vast amounts of data, such as Google and Facebook, are using that data advantage to create their own AI solutions. Solid examples of a Data Network.
-Some companies do a good job of integrating into their customer's workflows / processes and leveraging AI to assist with this; Clay is a good example. As a result, they have a Switching Cost Moat and as they add more and more features, potentially a Platform Network as well.
-Some AI companies like OpenAI with Chat-GPT have established incredibly strong Brand Moats.
-I expect that over time, as regulation around AI increases, we will see more Regulatory Moats and IP Moats in the AI space.
I wouldn't say Knowledge Moats are that robust in AI. Some companies are trying to build an edge by being better at prompting or working with existing AI models, but the underlying models are changing so fast that it's hard to have a lasting edge just from knowledge.
Great article! Your detailed breakdown of different types of business moats, along with historical examples, made complex concepts easy to grasp. I especially enjoyed the insights into how companies like Uber, Google, and Apple have built their moats. Looking forward to your next piece.
Kai - I think that it depends on the AI company in question. I think there are different moats each could attempt to build instead of all AI companies falling under a single moat. Some examples:
-Marketplaces often leverage AI (e.g. Amazon's recommendation engine).
-Many companies with vast amounts of data, such as Google and Facebook, are using that data advantage to create their own AI solutions. Solid examples of a Data Network.
-Some companies do a good job of integrating into their customer's workflows / processes and leveraging AI to assist with this; Clay is a good example. As a result, they have a Switching Cost Moat and as they add more and more features, potentially a Platform Network as well.
-Some AI companies like OpenAI with Chat-GPT have established incredibly strong Brand Moats.
-I expect that over time, as regulation around AI increases, we will see more Regulatory Moats and IP Moats in the AI space.
I wouldn't say Knowledge Moats are that robust in AI. Some companies are trying to build an edge by being better at prompting or working with existing AI models, but the underlying models are changing so fast that it's hard to have a lasting edge just from knowledge.
Great article :) Curious - where would some AI companies fit? Would they be in the "data moat" category or "knowledge moat"?
Great article! Your detailed breakdown of different types of business moats, along with historical examples, made complex concepts easy to grasp. I especially enjoyed the insights into how companies like Uber, Google, and Apple have built their moats. Looking forward to your next piece.